Pancreatico-biliary adenocarcinomas (PBA) have a poor prognosis. Diagnosis is usually achieved by imaging and/or endoscopy with confirmatory cytology. Cytological interpretation can be difficult especially in the setting of chronic pancreatitis/cholangitis. Immunohistochemistry (IHC) biomarkers could act as an adjunct to cytology to improve the diagnosis. Thus, we performed a meta-analysis and selected KOC, S100P, mesothelin and MUC1 for further validation in PBA resection specimens. Tissue microarrays containing tumour and normal cores in a ratio of 3:2, from 99 surgically resected PBA patients, were used for IHC. IHC was performed on an automated platform using antibodies against KOC, S100P, mesothelin and MUC1. Tissue cores were scored for staining intensity and proportion of tissue stained using a Histoscore method (range, 0–300). Sensitivity and specificity for individual biomarkers, as well as biomarker panels, were determined with different cut-offs for positivity and compared by summary receiver operating characteristic (ROC) curve. The expression of all four biomarkers was high in PBA versus normal ducts, with a mean Histoscore of 150 vs. 0.4 for KOC, 165 vs. 0.3 for S100P, 115 vs. 0.5 for mesothelin and 200 vs. 14 for MUC1 (p < .0001 for all comparisons). Five cut-offs were carefully chosen for sensitivity/specificity analysis. Four of these cut-offs, namely 5%, 10% or 20% positive cells and Histoscore 20 were identified using ROC curve analysis and the fifth cut-off was moderate-strong staining intensity. Using 20% positive cells as a cut-off achieved higher sensitivity/specificity values: KOC 84%/100%; S100P 83%/100%; mesothelin 88%/92%; and MUC1 89%/63%. Analysis of a panel of KOC, S100P and mesothelin achieved 100% sensitivity and 99% specificity if at least 2 biomarkers were positive for 10% cut-off; and 100% sensitivity and specificity for 20% cut-off. A biomarker panel of KOC, S100P and mesothelin with at least 2 biomarkers positive was found to be an optimum panel with both 10% and 20% cut-offs in resection specimens from patients with PBA.

Herein, we report the mutational spectrum of three breast cancer candidate genes (TP53, PIK3CA, and PTEN) using WES for identifying potential biomarkers. The WES data were thoroughly analyzed using SAMtools for variant calling and identification of the mutations. Various bioinformatic tools (SIFT, PolyPhen-2, Mutation Taster, ISPRED-SEQ, SAAFEQ-SEQ, ConSurf, PROCHECK etc.) were used to determine the pathogenicity and nature of the SNVs. Selected interaction site (IS) mutations were visualized in PyMOL after building 3D structures in Swiss-Model. Ramachandran plots were generated by using the PROCHECK server. The selected IS mutations were subjected to molecular dynamic simulation (MDS) studies using Gromacs 4.5. STRING and GeneMANIA were used for the prediction of gene-gene interactions and pathways. Our results revealed that the luminal A molecular subtype of the breast cancer was most common, whereas a high percentage of was Her2 negatives. Moreover, the somatic mutations were more common as compared to the germline mutations in TP53, PIK3CA, and PTEN. 20% of the identified mutations are reported for the first time from Khyber Pakhtunkhwa. In the enrolled cohort, 23 mutations were nonsynonymous SNVs. The frequency of mutations was the highest in PIK3CA, followed by TP53 and PTEN. A total of 13 mutations were found to be highly pathogenic. Four novel mutations were identified on PIK3CA and one each on PTEN and TP53. SAAFEQ-SEQ predicted the destabilizing effect for all mutations. ISPRED-SEQ predicted 9 IS mutations (6 on TP53 and 3 on PIK3CA), whereas no IS mutation was predicted on PTEN. The TP53 IS mutations were TP53^R43H, TP53^Y73X, TP53^K93Q, TP53^K93R, TP53^D149E, and TP53^Q199X; whereas for PIK3CA, the IS mutations were PIK3CA^L156V, PIK3CA^M610K, and PIK3CA^H1047R. Analysis from the ConSurf Web server revealed five SNVs with a highly conserved status (conservation score 9) across TP53 and PTEN. TP53^P33R was found predominant in the grade 3 tumors, whereas PTEN^p.C65S was distributed on ER+, ER-, PR+, PR-, Her2+, and Her2- patients. TP53^p.P33R mutation was found to be recurring in the 14/19 (73.6%) patients and, therefore, can be considered as a potential biomarker. Finally, these mutations were studied in the context of their potential association with different hormonal and social factors.

Background: Clinical translation of immunohistochemistry (IHC) biomarkers requires reliable and reproducible cutoffs or thresholds for interpretation of immunostaining. Most IHC biomarker research focuses on the clinical relevance (diagnostic, prognostic, or predictive utility) of cutoffs, with less emphasis on observer agreement using these cutoffs. From the literature, we identified 3 commonly used cutoffs of 10% positive epithelial cells, 20% positive epithelial cells, and moderate to strong staining intensity (+2/+3 hereafter) to use for investigating observer agreement. Materials and Methods: A series of 36 images of microarray cores stained for 4 different IHC biomarkers, with variable staining intensity and percentage of positive cells, was used for investigating interobserver and intraobserver agreement. Seven pathologists scored the immunostaining in each image using the 3 cutoffs for positive and negative staining. Kappa (κ) statistic was used to assess the strength of agreement for each cutoff. Results: The interobserver agreement between all 7 pathologists using the 3 cutoffs was reasonably good, with mean κ scores of 0.64, 0.59, and 0.62, respectively, for 10%, 20%, and +2/+3 cutoffs. A good agreement was observed for experienced pathologists using the 10% cutoff, and their agreement was statistically higher than for junior pathologists (P=0.02). In addition, the mean intraobserver agreement for all 7 pathologists using the 3 cutoffs was reasonably good, with mean κ scores of 0.71, 0.60, and 0.73, respectively, for 10%, 20%, and +2/+3 cutoffs. For all 3 cutoffs, a positive correlation was observed with perceived ease of interpretation (P<0.003). Finally, cytoplasmic-only staining achieved higher agreement using all 3 cutoffs than mixed staining patterns. Conclusions: All 3 cutoffs investigated achieve reasonable strength of agreement, modestly decreasing interobserver and intraobserver variability in IHC interpretation. These cutoffs have previously been used in cancer pathology, and this study provides evidence that these cutoffs can be reproducible between practicing pathologists.

Herein, we reported mutations in five DNA Damage Repair (DDR) i.e., TP53, ATR, ATM, CHEK1 and CHEK2 involved in OSCC using NG-WES and their analysis using bioinformatics tools. Out of 42 identified mutations, 16.7% are reported for the 1st time. A total of 28 nonsynonymous SNVs are identified. TP53 harbored the highest number of mutations followed by ATM, ATR, CHEK1 and CHEK2. Nine mutations (TP53^p.R43H, TP53^p.L125Q, TP53^p.R116Q, TP53^p.C110Y, TP53^p.L62F, ATR^p.H120Y, ATM^p.P1054R, ATM^p.D1853V, ATM^p.T2934N) were predicted highly pathogenic. SAAFEQ-SEQ predicted destabilizing effects for all mutations, while ISPRED-SEQ identified 09 IS mutations, 07 on TP53, 01 in ATR and 01 in CHEK1 with no IS mutations predicted for ATM and CHEK2. Among the IS mutations, only SNVs were used in MDS simulations. The gyration radius for all IS SNVs was larger for mutant as compared to the wild type indicating perturbed folding behavior of the mutant proteins. Structural deviations across the carbon back bone were noted by RMSD for mutant and wild type. The TP53 IS mutations include TP53^p.R116Q, TP53 ^p.C110Y, TP53^p.R43H, TP53^p.E214X, TP53^p.R210X, TP53 ^p.C110Afs*5 and TP53 ^p,S108Ffs*23 whereas ATR and CHEK1 IS mutations consist of ATR^p.M1932T and CHEK1^p.E76Kfs*21. ConSurf analysis revealed four SNVs with a high conservation score (9) on TP53 and ATM. TP53^p.P33R was predominantly associated with moderately differentiated tumors (84.60%), naswar users (86.60%) and positive family history of cancer (91.60%). The TP53^p.P33R, ATR^p.M211T and CHEK1^p.I437V mutations were found recurrently in 21/27 (77.7%), 20/27 (74.04%), and 27/27 (100%) patients, suggesting its potential biomarker applications in local screening.

Gene mutations are a source of genetic instability which fuels the progression of cancer. Mutations in BRCA1 and BRCA2 are considered as major drivers in the progression of breast cancer and their detection indispensable for devising therapeutic and management approaches. The current study aims to identify novel pathogenic and recurrent mutations in BRCA1 and BRCA2 in Pakhtun population from the Khyber Pakhtunkhwa. To determine the BRCA1 and BRCA2 pathogenic mutation prevalence in Pakhtun population from KP, whole exome sequencing of 19 patients along with 6 normal FFPE embedded blocks were performed. The pathogenicity of the mutations were determined and they were further correlated with different hormonal, sociogenetic and clinicopathological features. We obtained a total of 10 mutations (5 somatic and 5 germline) in BRCA1 while 27 mutations (24 somatic and 3 germline) for BRCA2. Five and seventeen pathogenic or deleterious mutations were identified in BRCA1 and BRCA2 respectively by examining the mutational spectrum through SIFT, PolyPhen-2 and Mutation Taster. Among the SNVs, BRCA1 ^p.P824L, BRCA2 ^{p. P153Q, p.I180F, p.D559Y, p.G1529R, p.L1576F, p.E2229K} were identified as mutations of the interaction sites as predicted by the deep algorithm based ISPRED-SEQ prediction tool. SAAFEQ-SEQ web-based algorithm was used to calculate the changes in free energy and effect of SNVs on protein stability. All SNVs were found to have a destabilizing effect on the protein. ConSurf database was used to determine the evolutionary conservation scores and nature of the mutated residues. Gromacs 4.5 was used for the molecular simulations. Ramachandran plots were generated using procheck server. STRING and GeneMania was used for prediction of the gene interactions. The highest number of mutations (BRCA1 7/10, 70 %) were on exon 9 and (BRCA2, 11/27; 40 %) were on exon 11. 40 % and 60 % of the BRCA2 mutations were associated Grade 2 and Grade 3 tumors respectively. The present study reveals unique BRCA1 and BRCA2 mutations in Pakhtun population. We further suggest sequencing of the large cohorts for further characterizing the pathogenic mutations.

Background: Oral squamous cell carcinoma (OSCC) may arise from premalignant oral lesions (PMOL) in most cases. Minichromosome maintenance 3 (MCM3) is a proliferative marker that has been investigated as a potential diagnostic biomarker in the diagnosis of oral cancer. Objectives: To evaluate the association of MCM3 expression, its clinicopathologic parameters and to identify snuff (also called naswar) as a potential risk factor for changes in MCM3 expression in PMOL and OSCC. Methodology: Immunohistochemistry (IHC) of MCM3 was performed on 32 PMOL, 32 OSCC and 16 normal controls after optimization of IHC methodology. Histoscore (0–300) was used as a scoring system and seven different cut-offs were identified for analyses. Data were analyzed using various statistical tests. Results: Among the seven cutoffs, 40% strong positive cells were found to be a better cut-off as they were associated with many pathological variables (Broder’s grade, Aneroth’s grade, and mitotic activity). The differential MCM3 expression in oral lesions (PMOL and OSCC) was statistically significant (p = 0.03). Moreover, MCM3 expression is raised with increased duration and frequency of snuff use. Conclusion: High MCM3 expression is associated with disease progression and is a potential indicator of malignant transformations from PMOL to OSCC. Moreover, the use of snuff is associated with MCM3 over-expression.